The output of stage one is a set of properties that hold for background relations. If a property holds for a relation, we generate the corresponding constraint to prohibit hypotheses that violate the constraint.
These constraints can potentially be used by any ILP system.
We implement our approach to work with Popper [1]}.
Popper is a natural choice because it frames the ILP problem as a constraint satisfaction problem.
Moreover, it learns recursive programs, supports predicate invention, and is open-sourceILASP [2]} is an alternative system but is closed-source and thus difficult to adapt..
We describe Popper and our modification named DiscoPopper.
